This article aims to show how a corpus driven theory that analyses speech through information units can better account for Discourse Markers (DM) identification and analysis. We propose that the speech flow can only be properly analyzed if segmented into utterances and tone units through prosodic parameters. Utterances correspond to speech acts and tone units to information units (IU); therefore, it is possible for DMs to be identified since they correspond to dialogic information units (DU). Each IU is submitted to different prosodic conditions in order to carry their function. This allows for: (i)&#160;identifying DUs; (ii) distinguishing different DUs, thus recognizing the specific function of each DM. We present data from comparable corpora from different Romance languages. The DM data are studied focusing on their functions, frequency, distribution and lexical fillers.